Image compressing apparatus

ABSTRACT

An image compressing apparatus employs a mean-separated normalized vector quantization method according to which, with respect to vector components corresponding to input images inputted from image sensors via a plurality of lines, encodes and outputs a scalar-quantized code of a mean value, a scalar-quantized code of a maximum scalar product value with each code word in a code book, and an index of one of the code words which yields a maximum scalar product value. In this image compressing apparatus, when the maximum scalar product value is less than a predetermined threshold value, in accordance with judgement by a comparator circuit, an output selecting circuit stops outputting the codes of the maximum scalar product value and of the index, and outputs only the code of the mean value. Therefore, when the image is uniform with pixels varying little in their luminance levels in compression processing unit blocks, code data to be outputted are restricted so that only data of the mean value are outputted. Consequently, it is possible to restrain degradation of the image and to considerably reduce data amount.

FIELD OF THE INVENTION

The present invention relates to an apparatus for compressing an imagesignal upon its transmission, recording and the like.

BACKGROUND OF THE INVENTION

Various methods are suggested for converting an image signal into adigital signal, which rarely deteriorates, upon its transmission,recording and the like. In accordance with these conversion methods,compressing methods are also suggested for, without directlytransmitting or recording the digital signal, compressing the dataamount to, for example, a range between a fraction of the amount and aseveral tenths of the amount in order to decrease its transmission timeand memory data amount.

A typical example of such encoding methods is the vector quantizationmethod, which works as explained below. First, an analog signal to becompressed is divided into compression processing unit blocks of, forexample, 6×6=36 pixels. Then those compression processing unit blocksare sequentially scanned to determine the signal level of each pixel,which in turn becomes the vector component xk of a K-dimensional inputvector x. Here k represents a pixel number, and k=1, 2, . . . , K. Inthis example K equals 36.

Meanwhile, a plural kinds of images are prepared in advance forlearning. A code word ci is defined as a vector for learning which isobtained in the same manner as above for image signals of the image forlearning. A code book b, composed of such code words ci which correspondto the respective signals, is then stored. Here i represents anidentification number, and i=1, 2, . . . , M. Hereinafter i will bereferred to as an index. Then the code word ci which is the closest tothe input vector x is chosen from the code words ci in the stored codebook b. Then only the index i of that chosen code word ci is transmittedor recorded.

Namely, the code word cI giving the smallest value for the equation:##EQU1## is determined and its index I is transmitted or recorded.

As a result, the data amount per 1 vector equals log₂ M (bits). Forexample, suppose that 256 (=M) code words are stored in the code book bfor the previously mentioned compression processing unit blocks ofK=6×6=36 pixels, since 256=2⁸, 8/36=0.22 (bit/pixel). Thus, the dataamount is reduced to 1/36 of the case where scalar quantization of 8bits is performed for each pixel.

The normalized vector quantization (also called as the gain/shape vectorquantization) method for compressing data amount has been created byfurther improving the vector quantization method. According to thenormalized vector quantization method, the size of the code words C1through CM in the code book B are 1. Namely,

    |Ci|=(Ci, Ci).sup.1/2 =1

The code word CI which produces a maximum value for the scalar productsof the input vector x and the code words Ci, namely, ##EQU2## isdetermined. Then the input vector x is expressed as:

    x=SQ{(x, CI)}·CI                                  (3)

wherein SQ{(x, CI)} is a scalar amount of the scalar product (x, CI).

The input vector x is expressed as Eq. (3) for the following reasons.Suppose that A is a scalar amount, since |Ci|² =1, the followingequation is obtained: ##EQU3## In the above equation, the relationshipbetween the second and third terms of the right side, |x|² and (x, Ci)²,is |(x, Ci)|² ≦|x|². Therefore, when the code word Ci equals the codeword CI which maximizes the scalar product (x, Ci), and A equals (x,Ci), the left side of Eq. (4) takes its minimum value, so SQ{(x, CI)}·CIbecomes the vector which is the closest to the input vector x.

Hence, the code book B necessary to both a compressing side and anextension side can be made smaller. Namely, the number of stored codewords M is reduced.

In addition, the mean-separated normalized vector quantization (alsocalled as the differential normalized vector quantization ormean/gain/shape vector quantization) method has been created andsuggested by further improving the normalized vector quantization methodin order to reduce the number of stored code words M. According to themean-separated normalized vector quantization method, the mean value μof the components of the input vector x is obtained from the followingequation: ##EQU4##

Next, a difference component vector X=(X1, X2, . . . , XK) is obtainedby subtracting the mean value μ from the input vector x as in thefollowing equation:

    X=x-μ·U                                        (6)

Note that U=(1, 1, . . . , 1).

Then, the code word CI maximizing the absolute scalar product value |(X,Ci)| is determined out of the code words Ci, unit-length code words inthe code book B used for the normalized vector quantization method. Themaximum value P of the scalar product (X, Ci) and the mean value μobtained in this manner are scalar-quantized, and the index I isbinarized so that codes are compressed and then transmitted or recorded.

In accordance with the compressed codes which have been transmitted orreproduced, an extension apparatus decodes an output vector xout in thefollowing manner:

    xout=Pa·CI+μa·U                       (7)

wherein Pa and μa represent, respectively, the maximum absolute value ofthe scalar-quantized scalar product value P and a quantized centralvalue of the mean value μ.

A typical conventional technique employing the above-mentionedmean-separated normalized vector quantization method is disclosed, forexample, in Japanese Laid-Open Patent Application No. 62-25577/1987(Tokukaishou 62-25577). According to this conventional technique, whenthe power of an input vector of the compression processing unit block isgreat, a vector quantization is carried out utilizing a code book withlong bits, that is, with large numbers of gradation: when the power issmall, data is compressed with the mean-separated normalized vectorquantization method.

As discussed so far, when the transmission rate is very small, such asan analog telephone line and cellular phone line, image signals of adynamic image can not be transmitted even with a mean-separatednormalized vector quantization method for compressing data amount,because the data is not compressed enough.

SUMMARY OF THE INVENTION

It is an object of the present invention to provide an image compressingapparatus which is able to further reduce data amount.

In order to achieve the above object, a first image compressingapparatus in accordance with the present invention has:

a plurality of scalar product value calculating sections for calculatingscalar product values of a difference component vector and each codeword, the difference component vector being generated by subtracting,from each vector component, a mean value of the vector components of aninput vector expressing image signals received for every predeterminedcompression processing unit block, the code word being generated fromimage signals of a plurality of kinds of predetermined images forlearning;

a scalar-quantization section for scalar-quantizing the mean value and amaximum scalar product value;

an encoding section for encoding an identification number of one of thecode words, the code word yielding the maximum scalar product valuethrough the calculation by the scalar product value calculating section;

a comparator section for judging whether the maximum scalar productvalue is not less than a predetermined threshold value; and

an output selecting section for, in accordance with the judgement by thecomparator section, outputting the quantization code of the mean valuefrom the scalar quantization section, the quantization code of themaximum scalar product value from the scalar quantization section andthe identification code of the code word from the encoding section whenthe maximum scalar product value is not less than the threshold value,and outputting only the quantization code of the mean value when themaximum scalar product value is less than the threshold value.

In order to achieve the above object, a second image compressingapparatus in accordance with the present invention has:

a mean value calculating section for calculating a mean value of vectorcomponents of an input vector expressing image signals received forevery predetermined compression processing unit block;

a mean value separating section for generating a difference componentvector by subtracting the calculated mean value from each of the vectorcomponents of the input vector;

a memory section for storing vectors for learning generated from imagesignals of a plurality of kinds of predetermined images for learning ascode words;

a scalar product value calculating section for calculating scalarproduct values of the difference component vector and each of the codewords;

a maximum scalar product value detecting section for detecting one ofthe code words, the code word yielding a maximum scalar product valuethrough the calculation;

a mean value quantization section for scalar-quantizing the mean value;

a gain quantization section for scalar-quantizing the maximum scalarproduct value;

a vector encoding section for encoding an identification number of thecode word yielding the maximum scalar product value;

a comparator section for judging whether the maximum scalar productvalue is not less than a predetermined threshold value;

an output selecting section for, in accordance with the judgement by thecomparator section, outputting the quantization code of the mean valuefrom the mean value quantization section, the quantization code of themaximum scalar product value from the gain quantization section and theidentification code of the code word from the vector encoding sectionwhen the maximum scalar product value is not less than the thresholdvalue, and outputting only the quantization code of the mean value whenthe maximum scalar product value is less than the threshold value.

The first and second image compressing apparatuses allows the outputselecting section to output only the quantization code of the mean valuewhen the maximum scalar product value is less than the predeterminedthreshold value, that is, when the image in the compression processingunit block is relatively uniform.

To describe more details, the image is divided into the compressionprocessing unit blocks having, for example, K pieces of pixels, and thecompression processing unit blocks are sequentially scanned to obtainsignal levels of the pixels, which in turn are designated as the vectorcomponents of a K-dimensional input vector. As the input vector thusobtained from the image signals is received, the mean value of thevector components is calculated first, and then the component differencevector is obtained by subtracting the mean value from each of the vectorcomponents of the input vector. Specifically, the calculation of themean value is carried out by the mean value calculation section of thesecond image compressing apparatus. Besides, the calculation of thedifference component vector is carried out by the mean value separatingsection of the second image compressing apparatus.

The scalar product value calculating section calculates the scalarproduct values of the code words and the difference component vectorobtained by the mean value separating section. From the results of thecalculation by the scalar product value calculating section, the maximumscalar product value detecting section detects the code word yieldingthe maximum value for the scalar product values corresponding to thecode words, that is, the code word which is closest to the input vector.Note that in the second image compressing apparatus, the code words arestored in the memory section as vectors for learning obtained from theimage signals of the plurality of kinds of predetermined images forlearning.

The mean value, the maximum scalar product value, and the identificationnumber of the code word yielding the maximum scalar product valueobtained in this manner are encoded for transmittance, recording and soon. More specifically, in the first image compressing apparatus, themean value and the maximum scalar product value are scalar-quantized bythe scalar quantization section, and the identification number isencoded into the identification code by the encoding section. Meanwhile,in the second image compressing apparatus, the mean value isscalar-quantized by the mean value quantization section, the maximumscalar product value is scalar-quantized by the gain quantizationsection, and the identification number is encoded into theidentification code by the vector encoding section.

Moreover, in the first and second image compressing apparatuses, upontransmittance, recording or so on, the comparator section judges whetherthe maximum scalar product value is less than the predeterminedthreshold value. In accordance with the judgement, the output selectingsection outputs the quantization code of the mean value, thequantization code of the maximum scalar product value and theidentification code when the maximum scalar product value is not lessthan the threshold value, and outputs only the quantization code of themean value when the maximum scalar product value is less than thethreshold value.

Therefore, when the image is almost uniform across the compressionprocessing unit block, the output of the quantization code of themaximum scalar product value and the identification code is stopped.Meanwhile, on the decompressing side, decoding into the image signals iscarried out with the code word of the identification code and the meanvalue outputted before the output is stopped. It is thus possible toreproduce an image which the viewer can not differentiate from an imagein a case where all the data are transmitted or recorded, to restraindegradation of the image signal, and to reduce the data amount to betransmitted, recorded and so on as much as possible.

The first and second image compressing apparatuses preferably has:

a low band buffer for generating a low band vector for every low bandcompression processing unit block composed of a plurality of compressionprocessing block units by receiving the mean values at a predeterminedcycle; and

a low band vector quantization section for vector-quantizing the lowband vector with the mean-separated normalized vector quantizationmethod,

wherein the output selecting section outputs a quantization code of alow band mean value, a quantization code of a low band maximum scalarproduct value and a low band identification code, i.e., anidentification number of the code word yielding the low band maximumscalar product value, instead of the quantization code of the meanvalue.

With the above arrangement, the mean-separated normalized vectorquantization is further carried out with the quantization code of themaximum scalar product value and the identification code obtained by thefirst or second image compressing apparatus as high band components andthe mean value of the smaller data amount per pixel as low bandcomponents. It is thus possible to further reduce the data amountwithout damaging the image quality.

The output selecting section in the first and second image compressingapparatuses preferably outputs selectively the quantization code of themean value, a quantization code of the low band mean value obtained byfurther vector-quantizing the mean value with the mean-separatednormalized vector quantization method, the quantization code of the lowband maximum scalar product value and the low band identification code.

With the arrangement, it is possible to switch the compression methodsaccording to whether the decompressing side (for example, a receiver ora reproducing apparatus) has an advanced function of decoding the codewhich is further vector-quantized from the mean value with themean-separated normalized vector quantization method.

Moreover, the scalar product value calculating section in the first andsecond image compressing apparatuses preferably includes an amplifierand capacitors corresponding to code components of each of the codewords, wherein the scalar product value calculating section calculatesscalar product values of the input vector and each of the code words ina parallel manner for each of the code words by inputting input signalsof a plurality of channels corresponding to the vector components to aterminal of each of the capacitors and connecting the other terminals ofthe capacitors commonly to the amplifier.

With the arrangement, the input signals of the channels corresponding tothe vector components are processed in a parallel manner by using thecode words as analog signals without being converted to digital signals.On the contrary, in a case where analog signals are processed afterbeing converted to digital signals, if the number of the code words isincreased, the calculation amount increases considerably. Therefore, thecalculation processing section is required to have a high performance,which leads to high cost and high power consumption. On the contrary,these problems are less likely to occur with analog signal processing inthe above arrangement.

More preferably, the capacities of the capacitors in the scalar productvalue calculating section are set in a capacity ratio as the quantizedcode components, wherein each of the scalar product value calculationsections includes a correction capacitor corresponding to quantizationerror caused by the capacitor and inputs a product of a electrostaticcapacity of the correction capacitor and the mean value to the amplifieras a correction value.

With the above arrangement, upon integration of the first and secondimage compressing apparatuses, even if, for example, a problem in theprocess causes the results of calculation of the scalar product valuesto include the quantization error due to the quantization error of thecode component corresponding to the capacitor capacity, it is possibleto correct the quantization error with the correction capacitor. It isthus possible to realize the correction of the quantization error byadding only the correction capacitors. Therefore, it is possible toexpress the code components highly accurately with small capacitorareas.

The first and second image compressing apparatuses preferably has:

an input vector inversion selecting section for inverting polarity ofthe input vector and selectively changing-over obtained inverted andnon-inverted values to be outputted; and

an inversion & comparator section for, in accordance with thechange-over operation of the input vector inversion selecting section,comparing the two scalar product values calculated by the scalar productvalue calculating section using the non-inverted and inverted valueswith each other, and outputting a greater scalar product value of thetwo and the code of the greater scalar product value.

With the above arrangement, the input vector inversion & comparatorsection selects a bigger value of the two scalar product values: one isobtained from the non-inverted value and the other from the input vectorwhose polarity is inverted by the input vector inversion selectingsection, i.e., the inverted value. The two scalar product values thusobtained are respectively equivalent to the scalar product values of theinput vector with the non-inverted and inverted values of the codecomponents. Therefore, it is possible to increase the indexes of thecode words by 1 bit, that is, double the number of the code words,without increasing the area needed for mounting capacitors by addingonly a simple circuit.

The code word employed in the first and second image compressingapparatuses is preferably one of a plurality of vectors for learningobtained in accordance with inputted image signals, the vector oflearning having a power greater than a predetermined threshold value andgreat changes in images in the compression processing unit blocks.

Therefore, the code word is composed of only a vector for learningobtained from an image which has relatively large change in the image(e.g., an image including an edge) and which is suitable as a vector forlearning, not including a blurry vector for learning obtained from animage which has a power less than the threshold value and little changein the image in the compression processing unit block and which is notsuitable as an image for learning. This prevents an objectionably blurryvector to be adopted as the code word and allows the code word which ishighly likely to agree with various inputted image signals to beincluded as the code word.

For a fuller understanding of the nature and advantages of theinvention, reference should be made to the ensuing detailed descriptiontaken in conjunction with the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram showing an electric arrangement of an imagecompressing apparatus and an associated image sensor of a firstembodiment in accordance with the present invention.

FIG. 2 is a drawing illustrating in what order luminance levels ofpixels in compression processing unit blocks on the image sensor areread in as vector components.

FIG. 3 is an electric circuit diagram showing a specific arrangement ofa maximum input detecting circuit provided in a maximum scalar productvalue detecting circuit in the image compressing apparatus.

FIG. 4 is a flow chart showing compressing operation of the imagecompressing apparatus.

FIG. 5 is a flow chart showing process of producing a code book forcompression by the image compressing apparatus.

FIG. 6 is a flow chart showing LBG algorithm process of obtaining codewords from a plurality of vectors for learning for producing the codebook.

FIG. 7(a) through 7(e) are drawings showing a concept of splittingalgorithm for initializing the code book in the LBG algorithm.

FIG. 8 is a block diagram showing an electric arrangement of an imagecompressing apparatus and an associated image sensor of a secondembodiment in accordance with the present invention.

FIG. 9 is a block diagram showing an electric arrangement of an imagecompressing apparatus and an associated image sensor of a thirdembodiment in accordance with the present invention.

FIG. 10 is a drawing illustrating in what order mean values ofcompression processing unit blocks provided in a low band compressionprocessing unit block on the image sensor are read in as vectorcomponents in the image compressing apparatus in FIG. 9.

FIG. 11 is a block diagram showing an electrical arrangement of a lowband buffer circuit which reads in the mean values as the vectorcomponents as shown in FIG. 10 in the image compressing apparatus inFIG. 9.

FIG. 12 is an electric circuit diagram showing a specific arrangement ofa sample & hold circuit provided in the low band buffer circuit shown inFIG. 11.

FIG. 13 is a block diagram showing a specific arrangement of a low bandvector quantization circuit provided in the image compressing apparatusshown in FIG. 9.

FIG. 14 is a flow chart showing compressing operation of high bandcomponents by the image compressing apparatus shown in FIG. 9.

FIG. 15 is a flow chart showing compressing operation of low bandcomponents by the image compressing apparatus shown in FIG. 9.

DESCRIPTION OF THE EMBODIMENTS

Referring to FIGS. 1 through 7, the following description will discuss afirst embodiment in accordance with the present invention.

FIG. 1 is a block diagram showing an electric arrangement of an imagecompressing apparatus 1 and an associated image sensor 2 of the firstembodiment in accordance with the present invention. The imagecompressing apparatus 1 compresses (encodes) an image signal from theimage sensor 2, and outputs code data obtained with the compression to atransmitter, recording device, and so on via an output line 3 in amanner described later.

The image sensor 2 is composed of a large number of photo diodes 4arranged in a matrix form. The photo diodes 4 in each column areconnected to a vertical transmission CCD (charge coupled device) 5, andan end of the vertical transmission CCD 5 is connected to a horizontaltransmission CCD 6. Analog voltages hold by elements of each of thehorizontal transmission CCDs 6 are outputted from the elements via abuffer Fk (k=1, 2, . . . , K) to a line Lk (k=1, 2, . . . , K).

As shown in FIG. 2, the photo diodes 4 in the image sensor 2 are dividedinto, for example, a plurality of compression processing unit blocks 7of K=6 pixels ×6 pixels=36 pixels. Output voltages of the photo diodes 4are read out from the compression processing unit blocks 7 in asequential manner by the vertical transmission CCDs 5 and the horizontaltransmission CCDs 6, and then outputted to the lines L1 through LK.Consequently, as shown in FIG. 2, the image compressing apparatus 1 isfed with a K-dimensional input vector x whose vector components aresignal levels x1, x2, . . . , xK corresponding to luminance levels of anobject created in the respective photo diodes 4.

The image compressing apparatus 1 roughly has a mean value calculatingcircuit 11, a scalar product value calculating circuit 12, a maximumscalar product value detecting circuit 13, an A/D converters 14 and 15,an index encoding circuit 16, a comparator circuit 17 and an outputselecting circuit 18.

The mean value calculating circuit 11 includes a differential amplifierE0 and K pieces of unit capacitors H0k (k=1, 2, . . . , K as alreadymentioned) in accordance with the number of the dimension K of the inputvector x. The unit capacitors H0k are connected at one of their ends tothe inversion input terminal of the differential amplifier E0 via aninput line S0, and at the other ends to the respective lines Lk. Thedifferential amplifier E0 is grounded at its non-inversion inputterminal, allowing the ground level to function as the reference voltagevref. The non-inversion input terminal and output terminal of thedifferential amplifier E0 are connected with each other by a feedbackcapacitor h0.

Here, letting vk represent an input voltage from the line Lk, vorepresent an output voltage of the differential amplifier E0, H0k and h0respectively represent electrostatic capacities of the unit capacitorH0k and of the feedback capacitor h0, Eq. (8) is obtained according tothe principle of conservation of charge at the contact points of one ofthe ends of the unit capacitors H0k and the non-inversion input terminalof the differential amplifier E0: ##EQU5## This explains that scalarproduct values of vector components (v1-vref, v2-vref, . . . vK-vref)and their coefficients (-H01/h0, -H02/h0, . . . , -H0K/h0) can becalculated as (vo-vref).

Consequently, supposing that H0k/h0=1/K for all the unit capacitors H0k,the output voltage vo of the differential amplifier E0 to the line LAequals the mean value of voltages of the lines L1 through LK. The outputvoltage vo is inputted to the A/D converter 14 (a mean valuequantization section). Therefore, the mean value of the voltages of thelines L1 through LK (i.e., the mean value of the vector components x1through xK of the input vector x) are scalar-quantized and outputted bythe A/D converter 14. The outputted quantized codes are inputted to theoutput selecting circuit 18.

The scalar product value calculating circuit 12 includes a plurality (ipieces) of scalar product value calculating sections Ri (i=1, 2, . . . ,M). Each of the scalar product value calculating sections R1 through RMincludes (1) K pieces of code component capacitors H11, H12, . . . ,H1K; H21, . . . , H2K; . . . ; and HM1, . . . , HMK, and (2) twodifferential amplifiers E1a and E1b; E2a and E2b; . . . ; and EMa andEMb. Hereinafter, H11 through H1K provided in R1 will be referred to asH1; H21 through H2K in R2 as H2; and so on. All the code componentcapacitors will be exclusively referred to as Hik.

In the scalar product value calculating section R1, the code componentcapacitors H11 through H1K are connected at one of their ends to a lineS1a or S1b, and at the other ends to respective lines L1 through LK. Thelines S1a and S1b are connected respectively to the inversion inputterminals of the differential amplifiers E1a and E1b. The non-inversioninput terminals of the differential amplifiers E1a and E1b are grounded.The inversion input terminals and the output terminals of thedifferential amplifiers E1a and E1b are respectively connected with eachother via feedback capacitors h1a and h1b. The output of thedifferential amplifier E1a is fed to the inversion input terminal of thedifferential amplifier E1b via a capacitor h1c. The capacitors h1a, h1band h1c are designated to have the same electrostatic capacities.

As a result, the output of the differential amplifier E1a is invertedand amplified by the differential amplifier E1b with gain 1 before beingoutputted. The code component capacitors H11 through H1K haveelectrostatic capacities which make the above coefficients positivecoefficients when connected to the line S1a, and have electrostaticcapacities which make the above coefficients negative coefficients whenconnected to the line S1b. This allows the maximum scalar product valuedetecting circuit 13 to be fed with an output voltage in accordance withthe scalar product value. The rest of the scalar product valuecalculating sections R2 through RM have the same arrangement, and theiroutputs are fed to the maximum scalar product value detecting circuit13.

Each of the code component capacitors H1, H2, . . . , HM is arranged inthe respective scalar product value calculating section R1 through RM sothat the total electrostatic capacity of the positive coefficients andthat of the negative coefficients share the same absolute value.Therefore, the code component capacitors H1 through HM in the scalarproduct value calculating sections R1 through RM are mean-separated codewords. Since a mean value is separated from each of the code componentcapacitors H1 through HM in the scalar product value calculatingsections R1 through RM as mentioned above, the voltages outputted to thelines S1a and S1b; . . . ; and SMa and SMb are equivalent to levels fromwhich the mean value obtained from the unit capacitors H01 through H0Kin the mean value calculating circuit 11 is already subtracted. Thescalar product value calculating circuit 12 also functions as a meanvalue separating section. In addition the scalar product valuecalculating circuit 12 functions as a memory section having a code bookof M pieces of code words.

The maximum scalar product value detecting circuit 13 has a maximuminput detecting circuit 21 and switching elements Ti (i=1, 2, . . . , Mas already mentioned) corresponding to the respective scalar productvalue calculating sections Ri. Output lines Yi corresponding to therespective scalar product value calculating sections Ri extend from themaximum input detecting circuit 21. The maximum input detecting circuit21 outputs a high-level output only to the output line of the channelcorresponding to the scalar product value calculating section producingthe highest input voltage of all the voltages inputted from the scalarproduct value calculating sections Ri, and turns all the other channelsto a low level.

The output lines Yi are connected to the index encoding circuit 16 (avector encoding section). The index encoding circuit 16 converts theindex of the channel which is judged to have the maximum scalar productvalue into binary codes, and then outputs the binary codes to the outputselecting circuit 18.

The output lines Yi are connected to the respective gates of theswitching elements Ti. Therefore, the highest voltage of all the inputvoltages from the scalar product value calculating sections Ri isselected by the switching elements Ti, and then inputted to the A/Dconverter 15 (a gain quantization section). The voltage level isscalar-quantized by the A/D converter 15 and then inputted to the outputselecting circuit 18.

Moreover, the voltage selected by the switching elements Ti is inputtedto one of the terminals of the comparator circuit 17. A referencevoltage source 19 is connected to the other terminal of the comparatorcircuit 17. Therefore, the comparator circuit 17 judges if the maximumvalue of the scalar product values calculated by the scalar productvalue calculating circuit 12 is not less than a threshold valuedesignated by the reference voltage source 19. If the maximum value isnot less than the threshold value, the comparator circuit 17 feeds ahigh level output to the output selecting circuit 18 via a line 20,whereas if the maximum value is less than the threshold value, thecomparator circuit 17 turns the line 20 to a low level.

If the line 20 is in the high level, the output selecting circuit 18outputs, to the output line 3, code data of the mean value and of themaximum scalar product value inputted from the A/D converters 14 and 15,and index code data about the scalar product value calculating sectionproducing the maximum scalar product value. On the other hand, if theline 20 is in the low level, the output selecting circuit 18 outputsonly the code data of the mean value from the A/D converter 14 to theoutput line 3.

FIG. 3 is an electric circuit diagram showing a specific arrangement ofthe maximum input detecting circuit 21, which includes basic circuits αicorresponding to respective analog input voltages Vi of i pieces ofchannels.

The basic circuit αl includes a detection section 31 having five MOSfield effect transistors Q1 through Q5, and a feedback currentgenerating circuit 32 having four field effect transistors Q6 throughQ9. In the detecting section 31, the input voltage V1 from the scalarproduct value calculating section R1 is fed to the gate of the N-typetransistor Q1, and the drain of the transistor Q1 is connected to thedrain and the gate of the P-type transistor Q2.

The source of the transistor Q2 is connected to a power supply line 22(one of the two power supply lines) maintained at a high level Vdd. TheP-type transistor Q3 of the same kind with the transistor Q2 is providedcorrespondingly to the transistor Q2. The transistors Q2 and Q3 form acurrent mirror circuit. The gates of the transistors Q2 and Q3 areconnected to the drain of the transistor Q1. The source of thetransistor Q3 is connected to the power supply line 22, and its drain isconnected to the drain of the N-type transistor Q4.

A predetermined constant voltage Vb2 is applied to the gate of thetransistor Q4, and the source of the transistor Q4 is connected to theother power supply line 23 of a ground level. An output voltage Vol inaccordance with the impedances of the transistors Q3 and Q4 is outputtedfrom the contact point 24 of the transistors Q3 and Q4. The source ofthe transistor Q1 is connected to the drain of the N-type transistor Q5.The source of the transistor Q5 is connected to the power supply line23, and a predetermined constant voltage Vb1 is applied to the gate ofthe transistor Q5.

The output voltage Vol from the contact point 24 is inputted to thefeedback current generating circuit 32, being inputted to the gate ofthe N-type transistor Q7. The source of the transistor Q7 is connectedvia the N-type transistor Q6 to the power supply line 23. Apredetermined constant voltage Vb3 is applied to the gate of thetransistor Q6. Therefore, a bias current I6 flowing through thetransistor Q6 is specified by the constant voltage Vb3 so as to beconstant.

The drain of the transistor Q7 is connected to the power supply line 22via the P-type transistor Q8. The P-type transistor Q9 is provided tomake a pair with the transistor Q8. The transistors Q8 and Q9 form acurrent mirror circuit. The transistor Q9 positively feeds back, to acontact point 25 of the transistors Q1 and Q5, a feedback current IFcorresponding to a current flowing to the transistor Q7.

The other basic circuits α2 through αM are arranged in the same manneras is the basic circuit αl. The contact points 25 of the basic circuitsαi are all maintained at the same potential by a connecting line 27. Thecontact points 26 of the transistors Q7 and Q6 of the basic circuits αiare all maintained at the same potential by a connecting line 28.

An N-type transistor Q10 is provided for supplying the bias currents I6of the transistors Q6 of all the basic circuits αi. The gate and drainof the transistor Q1O are connected to the power supply line 22 of thehigh level Vdd.

The source of the transistor Q10 is connected to the drains of thetransistors Q6, that is, the connecting line 28. The transistors Q1through Q10 operate in a saturation area.

In the maximum input detecting circuit 21 arranged as discussed above,operation of the detecting section 31 is described in detail first. Thebias current I5 flowing through the transistor Q5 is specified by theconstant voltage Vb1 in the above mentioned manner. Besides, thetransistors Q5 are connected in parallel with each other by theconnecting line 27. The source voltage of the transistor Q1 is,therefore, specified to a value according to which the feedback currentIF from all the transistors Q9, the sum total M·I5 of currents I5flowing through the transistors Q5, and a current I1 corresponding tothe difference between the input voltage Vi and the source voltage ofthe transistor Q1 are balanced.

Consequently, a voltage corresponding to the difference between theimpedance of the transistor Q3 through which a current I3 flows and theimpedance of the transistor Q4 through which the current I4 specified bythe constant voltage Vb2 flows is outputted as an output voltage Voi outof the contact point 24, and inputted to the gate of the transistor Q7.Also, consequently, the transistor Q7 receives a current I7 from thetransistor Q8. The current I7 corresponds to the difference between thesource voltage of the transistor Q7 and the Voi inputted to thetransistor Q7. The source voltage of the transistor Q7 corresponds to acurrent I10 flowing through the transistor Q10 and to the sum total M·I6of the currents I6 specified by the constant voltages Vb3 in thetransistors Q6 connected in parallel with each other. Therefore, thecurrent I7 is positively fed back Q9 to the contact point 25 as thefeedback current IF specified by a ratio of currents flowing through thetransistors Q8 and Q9.

Therefore, as the output voltage Voi becomes higher than a sum of thevoltage of the connecting line 28 and the threshold voltage Vth requiredto allow the MOSFET to conduct, the feedback current generating circuit32 positively feeds back a greater feedback current IF to the contactpoint 25. Therefore, as the output voltage Voi becomes higher, thecurrent I1 flowing through the transistor Q1 (i.e., the current I3flowing through the transistor Q3) decreases. Meanwhile, since thetransistor Q7 is turned off as the output voltage Voi becomes lower thanthe sum voltage, the bias current I6 of the transistor Q6 is suppliedfrom the transistor Q10. The operation is conducted sequentially by thebasic circuits in ascending order in terms of the channels of the inputvoltages Vi. As a result, only the basic circuit with the maximum inputoutputs a high level as the output voltage Voi, and the maximum value isthus selected.

FIG. 4 is a flow chart illustrating compressing operation of the imagecompressing apparatus 1 arranged in the above manner. Output voltages ofthe photo diodes 4 are scanned sequentially by the CCDs 5 and 6, and theimage signal is inputted from the image sensor 2 to form the36-dimensional input vector x illustrated in γl for every compressionprocessing unit block 7. The photo diodes 4, CCDs 5 and 6, and thebuffers F1 through F36 and the like output the image signal inaccordance with the luminance level of the inputted image (for example,with resolution of 256 gradations).

The image signals are inputted to the mean value calculating circuit 11,and their mean value μ is calculated in the step β1 according to Eq.(5). A mean value signal illustrated in γ2 is outputted from the meanvalue calculating circuit 11.

The image signal is inputted to the scalar product value calculatingcircuit 12. First, in the step β2, the mean value μ is subtracted fromthe vector components x1 through x36 to generate a difference signalcorresponding to a difference component vector X=(X1, X2, . . . , X36)illustrated in γ3. Next, in the step β3, in the scalar product valuecalculating sections R1 through R32, calculation of scalar productvalues of the difference signal and each of the code words C1 throughC32 (illustrated in γ4) is carried out by the mean-separated codecomponent capacitors H1 through H36.

In the step β4, in the maximum scalar product value detecting circuit13, the code word CI which yields the maximum scalar product value P isdetected out of the scalar product values calculated in the step β3.After the maximum scalar product value P is obtained, in the step β5, inthe comparator circuit 17, the maximum scalar product value P and thethreshold value Vthl corresponding to the output voltage of thereference voltage source 19 are compared. If the maximum scalar productvalue P is not less than the threshold value Vth1, a judgement flag f isset to 1. If the maximum scalar product value P is less than thethreshold value Vth1, a judgement flag f is reset to 0.

In the step β6, as illustrated in γ5, in accordance with the judgementflag f, the A/D converters 14 and 15, the index encoding circuit 16, andthe output selecting circuit 18 output the code data of the mean valueμ, the index I and the maximum scalar product value P along with thecode data of the judgement flag f if the judgement flag f is 1, andoutput only the code data of the mean value μ along with the code dataof the judgement flag f if the judgement flag f is 0. The judgement flagf is expressed in 1 bit, for example, the mean value μ and the index Iare expressed in 5 bits, and the maximum scalar product value P isexpressed in 3 bits.

The code data fed from the output selecting circuit 18 to the outputline 3 is given to and transmitted by a transmitter, or given to andrecorded by a recording apparatus. Therefore, in accordance with thejudgement flag f, the code data received by a receiver, or reproduced bya reproducing apparatus are decoded from the mean value μ, the index I,and the maximum scalar product value P into the image signals of thecompression processing unit blocks 7 if the judgement flag f is 1, andare decoded from the mean value μ if the judgement flag f is 0. Theimages decoded from the compression processing unit blocks 7 aresequentially arranged to be at places predetermined on the image to bedecoded, and a decoded image is thus produced.

Here, supposing that the code word CI yielding the maximum scalarproduct value P equals (CI1, CI2, . . . , CIK), since each code word Ciis mean-separated, the following equation is obtained: ##EQU6## wherein|X| and |C| are absolute values of the difference component vector X andof the code word CI respectively. Since CI is a mean-separated vector asdiscussed earlier, 0≦(X/|X|,CI)≦1. Here, supposing that (X/|X|,CI)=cosθ, this cos θ can be considered to be an indicator for the closenessbetween the input vector x and the reference code word CI.

When the maximum scalar product value P is less than the threshold valueVth1, according to Eq. (10), |X| is relatively small, or cos θ is small.If cos θ is small, it means that the code word CI which is close to thedifference component vector X does not exist in the code book B.Therefore, if a proper code book B is selected (details follow) so thatany given difference component vector X can be approximated by at leastone code word Ci, when P<Vth1, it is considered that |X| is small, i.e.,that the power of the difference component vector X is small. In thiscase, the viewer can not recognize the difference in quality between thecase where the image output vector xout of the compression processingunit blocks 7 is decoded according to Eq. (7), xout=Pa·CI+μa·U, and thecase where the image output vector xout is decoded according to theequation: xout=μa·U.

Therefore, in the present invention, as described earlier, all the codedata are arranged to be outputted if P≧Vth1, whereas only the code dataof the mean value μ are arranged to be outputted if P<Vth1. Thus, whenthe compression processing unit block where P<Vth1 occurs more often,the data amount can be made smaller and the compression rate can beimproved.

Referring to FIG. 5, the following description will discuss how toproduce the code book B capable of having the code word CI which makesthe cos θ greater, that is, the code word CI which is highly likely toapproximate the difference component vector X. This operation is carriedout by the manufacturer who produces the code book B for compressing anddecompressing

A large number of images for learning are divided into compressionprocessing unit blocks 7. Then, an input vector xtn arranged as in FIG.2, whose vector components xtnk (n=1, 2, . . . , N) are data expressingluminance level of each pixel of the compression processing unit block 7in 8 bits, i.e., 256 tones is read in. First, in the step β11, a meanvalue μtn is obtained according to Eq. (5), and the mean value μtn isseparated from each vector component xtnk as in the following equationin order to obtain a difference component vector Xtn:

    Xtn=xtn-μtn=(Xtn1, Xtn2, . . . , XtnK)                  (11)

Next, in the step β12, the vector power |Xtn| of the differencecomponent vector Xtn is calculated according to Eq. (12).

    |Xtn|=(Xtn1.sup.2 +Xtn2.sup.2 +. . . +XtnK.sup.2).sup.1/2(12)

In the step β13, it is judged whether the power |Xtn| is not less than apredetermined threshold value Vth2. Only the difference component vectorwith a power not less than the threshold value Vth2 is used as a vectorXtn for learning. In the step β14, the code book B illustrated in γ11 isproduced according to the LBG (Linde, Buzo and Gray) algorithm (detailsfollow).

According to the LBG algorithm, the space formed by the many vectorsXt1, Xt2, . . . , XtN for learning is divided into a plurality of areas(called levels). In the above example, the space is divided into Mpieces of areas: r1 through rM. Then, representative vectors X01, X02, .. . , X0M are determined so as to minimize the sum of distances betweenthe representative vectors and all the vectors for learning included inthe respective areas r1 through rM. The produced representative vectoris used as the code word Ci in the present invention. In the scalarproduct value calculating sections R1 through RM, capacities of the codecomponent capacitors Hil through HiK are set in accordance with the8-bit, or 256-tone, data of the code components Cil through CiK of theobtained code word Ci.

FIG. 6 is a flow chart illustrating process of the LBG algorithm. In thestep β21, the number K of dimensions, the number M of levels and athreshold value ε for convergence judgment are initialized. Also, avariable m (m=0, 1, 2, . . . ) representing the number of renewals ofthe divided areas is reset to 0, and an initial distortion D(⁻¹) is setto +.sup.∞. Moreover, the code book B composed of the quantizationrepresentative vectors X01 through X0M is set to the initial conditioncode book B.sup.(0) obtained with a splitting algorithm (detailsfollow).

In the step β22, the code book B.sup.(m) is fixed and the divided areasr.sup.(m) are determined. Then distances (i.e., distortions) between thevectors for learning included in the divided areas r.sup.(m) in thatdividing state and the quantization representative vectors included inthose divided areas r.sup.(m) are obtained, and so is the mean valueD.sup.(m) of those distortions. In the step β23, a rate of changebetween the mean value D.sup.(m-1) of the distortions in the dividingstate of the divided areas r.sup.(m-1) of the preceding time and themean value D.sup.(m) of the distortions in the dividing state of thedivided areas r.sup.(m) of the present time is obtained. Then it isjudged whether the rate of change is below the threshold value ε forconvergence judgment. If the rate of change is below the threshold valueε, the quantization representative vectors are set as the code words,and the setting of the code book B is finished. If not, the algorithmproceeds to the step β24.

In the step β24, the divided areas r.sup.(m) are fixed, and thequantization representative vectors in the code book B.sup.(m) are setas respective center-of-gravity vectors in the divided areas r.sup.(m)In the step β25, the variable m is added with 1 and then the algorithmreturns to the step β22. The quantization representative vectors withthe minimum distortions from the vectors for learning in the dividedareas r1 through rM (the divided areas of the level number M) areobtained by repeating the steps β22 through β25 in this manner, and setas the code words Ci of the code book B. The capacities of the codecomponent capacitors Hi1 through HiK are determined in accordance withthe vector components of the code words Ci produced in this manner.

FIG. 7(a) through 7(e) illustrate the concept of splitting algorithm, amethod for obtaining the initial code book B.sup.(0). With the splittingalgorithm, two code words which are close to each other (e.g., CM1 andCM2) are produced out of the code words C1 through CM in the code bookB(M) of M levels by using a micro vector δ according to the followingequation.

    CM1=CM-δ

    CM2=CM+δ                                             (13)

First, as shown in FIG. 7(a), center-of-gravity vectors of all thevectors Xt1 through XtN for learning are determined and set as arepresentative point Z1 of the level 1.

Next, as shown in FIG. 7(b), the representative point Z1 is displaced bythe predetermined dividing parameter δ to determine representativepoints Z21a and Z22a of the level 2.

Then, the distances between the vectors Xt1 through XtN for learning andeither of the two representative points Z21a and Z22a are calculated. Asshown in FIG. 7(c), boundaries of areas r21 and r22 to which the vectorsXtn for learning belong are changed so as to minimize the sum of thedistances between each of the vectors Xtn for learning and either of thetwo representative points Z21a and Z22a. The change of the boundaries isrepeated until the rate of change of the sum of the distances does notexceed a predetermined value of ε.

Dividing of the vector space is thus completed. Then, in the same manneras in FIG. 7(a), as shown in FIG. 7(d), center-of-gravity vectors of thevectors for learning belonging to the areas r21 and r22 are determinedin the areas r21 and r22, and the mean values of those center-of-gravityvectors are set as representative points Z21 and Z22 at the level 2.

Next, as shown in FIG. 7(e), the representative points Z21 and Z22 aredisplaced by the dividing parameter δ to determine representative pointsZ41, Z42, Z43 and Z44 at the level 4. In the same manner as above, theareas are divided, and representative points are determined. Thisoperation is repeated until the desired exponent level number (=codeword number) M of 2 is attained.

Table 1 shows results of experiments by the inventors of the presentinvention. The code words Ci used in the experiments are learned underthe following conditions: (1) the number N of vectors for learningcorresponding to the compression processing unit blocks 7 obtained froma large number of images for learning composed of 512 pixels ×512 pixelsis set to 28900, (2) the number K of dimensions of the vectors Xtn forlearning is set to 36, (3) the number M of levels is set to 32, whichequals the number of code words, (4) the dividing parameter δ is set to0.1, (5) the convergence judgement value ε is set to 0.0001. Three kindsof experiments I, II and III are conducted with respect to sample images(i) through (vi) which are different from the above mentioned images forlearning.

In the experiment I, the threshold value Vth 2 used during learning isnot set. That is, all the input vectors xtn are used as vectors Xtn forlearning. In addition, the threshold value Vth 1 used during compressionof code data is not set. Therefore, all the code data are outputted atany time. In the experiment II, the threshold value Vth 2 is not set,and only the threshold value Vth 1 is set. In the experiment III, boththreshold values Vth2 and Vth1 are set. In the Table 1, numbers in theupper half of every block show data amount per one pixel in bits/pixelafter compression. Numbers in the lower half show S/N ratios, or imagequality, in dB.

                                      TABLE 1                                     __________________________________________________________________________           Sample                                                                             Sample                                                                             Sample                                                                             Sample                                                                             Sample                                                                             Sample                                                                             Average                                         Image 1                                                                            Image 2                                                                            Image 3                                                                            Image 4                                                                            Image 5                                                                            Image 6                                                                            Value                                    __________________________________________________________________________    Experiment 1                                                                         0.4444                                                                             0.4444                                                                             0.4444                                                                             0.4444                                                                             0.4444                                                                             0.4444                                                                             0.4444                                          25.341                                                                             23.885                                                                             23.268                                                                             16.978                                                                             22.726                                                                             23.035                                                                             23.372                                   Experiment 2                                                                         0.1744                                                                             0.1944                                                                             0.2659                                                                             0.2994                                                                             0.1937                                                                             0.1609                                                                             0.2148                                          24.277                                                                             22.823                                                                             22.744                                                                             16.865                                                                             22.685                                                                             22.270                                                                             22.944                                   Experiment 3                                                                         0.1726                                                                             0.1958                                                                             0.2961                                                                             0.2669                                                                             0.1815                                                                             0.1602                                                                             0.2122                                          24.270                                                                             22.943                                                                             23.030                                                                             16.909                                                                             22.396                                                                             28.223                                                                             22.962                                   __________________________________________________________________________

As is clear from the mean values of the experiments II and III, bysetting the threshold value Vth2 during learning, the data amount afterthe compression is reduced and the image quality is also improved. As isclear from the mean values of the experiments I and II, the data amountis reduced almost by half without damaging the image quality by settingthe threshold value Vth1 during compression.

As discussed so far, when relatively uniform images are obtained for allthe compression processing unit blocks 7 (e.g., when the maximum scalarproduct value P of the input vector x corresponding to the inputtedimage and the code words Ci in the code book B is below the thresholdvalue Vth1), the image compressing apparatus 1 in accordance with thepresent invention outputs only the mean value μ of the vector componentsxk as the code data. On the contrary, when images with relatively largechange (e.g., images including an edge where the threshold value Vth1 isexceeded) are obtained, the image compressing apparatus 1 outputs, aswell as the mean value μ, the maximum scalar product value P and theindex I of the code word CI yielding the maximum scalar product value Pas the code data. Therefore, the data amount is considerably reducedwithout damaging the image quality to such an extent that the viewer canrecognize the quality difference.

Since upon learning the code words Ci in the code book B, only the inputvectors xtn having power |Xtn| not less than the threshold value Vth2are set as the vectors Xtn for learning, relatively uniform and blurryimages across the compression processing unit blocks 7 which are notsuitable for learning are eliminated, and only images with relativelygreat change which are suitable for learning can be used. Therefore, thecode book B does not include objectionably blurry images. It is alsopossible to store the code words which are highly likely to agree withvarious inputted image signals.

Referring to FIG. 8, the following description will discuss a secondembodiment in accordance with the present invention.

FIG. 8 is a block diagram showing an electric arrangement of an imagecompressing apparatus 1a and an image sensor 2 of the second embodimentin accordance with the present invention. The image compressingapparatus 1a is similar to the image compressing apparatus 1 discussedabove. Therefore, corresponding segments are indicated by the samereference numerals and description thereof is omitted. Attention shouldbe paid where in the image compressing apparatus 1a, correctioncapacitors Hcia and Hcib (will be generically referred to as Hc) forcorrecting quantization error of a code book (detailed descriptionfollows) are provided in each scalar product value calculating sectionRai in a scalar product value calculating circuit 12a.

In the image compressing apparatus 1 discussed above, each of the scalarproduct value calculating sections Ri in the scalar product valuecalculating circuit 12 realizes the code components Cik with a codecomponent capacitor Hik. The capacitor, however, usually occupies quitea large area in an integrated circuit chip. Therefore, in an arrangementwhere each of the code component capacitors Hik is realized byselectively using a large number of unit capacitors in accordance withgradient of the code components Cik, it is necessary to make the unitcapacitors very small. Alternatively, it is possible to realize the codecomponents Cik by making a quantized capacitor ratio Hi1:Hi2:Hi3: . . .:Hik equal, for example, 1:2:4: . . . :2. Nevertheless, if the unitcapacitors are made too small, it becomes difficult to achieve accuracyin accordance with the gradient with the present processing technology.Consequently, the quantized capacitor ratio is used.

Here, supposing that the code component capacitors Hik are not quantizedand exactly correspond to the desired code components Cik, the scalarproduct value of the difference component vector X and the code word Ciis given by the following equation: ##EQU7## Supposing that there occursno quantization error, Eq. (15) is obtained: ##EQU8## Therefore, Eq.(14) is rearranged as: ##EQU9##

Therefore, this scalar product value equals the result of the scalarproduct value calculation directly using the input vector x shown in Eq.(2). Therefore, as shown in the image compressing apparatus 1 discussedabove, even in the arrangement where the input vector x is directlyinputted to each of the scalar product value calculating sections Riwithout separating the mean value μ, it is possible to calculate thescalar product value of the difference component vector X and each ofthe code words Ci in an equivalent manner.

Nonetheless, if the code words Ci composed of the quantized capacitorsas discussed above is used, the scalar product value of the code wordsCi and the difference component vector X is given by the followingequation: ##EQU10##

Therefore, the result from directly using the input vector x from theimage sensor 2 as an input to each of the scalar product valuecalculating sections Ri is different from the result from using themean-separated difference component vector X. Therefore, if quantizationis carried out when the code component capacitors Hik are mounted on anintegrated circuit, there occurs error in calculation, or selection of awrong code word, causing different compression result.

Therefore, in the image compressing apparatus 1a, Eq. (18) is usedinstead of Eq. (17) in order to correct the quantization error.##EQU11##

In other words, the quantization error, -μΣ Cik!, is corrected bysetting a correction term, +μΣ Cik!.

For example, in the scalar product value calculating section Ra1, acorrection capacitor Hc1b is provided to a line S1b in order to correctquantization error caused by a positive coefficient code componentcapacitor H1⁺, while a correction capacitor Hc1a is provided to a lineS1a in order to correct quantization error caused by a negativecoefficient code component capacitor H1⁻. The correction capacitors Hc1aand Hc1b are connected at one of their ends to the lines S1a and S1b,respectively, and are fed at the other ends with an output from the meanvalue calculating circuit 11 which is outputted to the line LA. In thismanner, it is possible to carry out correction in accordance with thecorrection term, +μΣ Cik!.

As discussed above, even if the input vector x from the image sensor 2is directly inputted to each of the scalar product value calculatingsections Rai, it is possible to obtain the scalar product value which isequivalent to the scalar product value obtained in the case where thedifference component vector X is inputted after the mean value μ issubtracted, and to correct the code book quantization error withoutpaying special attention to the quantization error in the code book byadding only correction capacitors Hc1a, Hc1b; . . . ; HcMa, HcMb of asimple arrangement to the scalar value calculating sections Rai inaccordance with the quantization error -μΣ Cik! in the code book.

Referring to FIGS. 9 through 15, the following description will discussa third embodiment in accordance with the present invention.

FIG. 9 is a block diagram showing an electric arrangement of an imagecompressing apparatus 1b and an associated image sensor 2 of the thirdembodiment of the present invention. The image compressing apparatus 1bis similar to the image compressing apparatus 1a discussed above.Therefore, corresponding segments are indicated by the same referencenumerals and description thereof is omitted. Attention should be paidwhere in the image compressing apparatus 1b, (1) polarity of an inputsignal of signal level xk outputted to a line Lk1 from each buffer Fk ofthe image sensor 2 is switched between non-inversion and inversion andoutputted to the line Lk by an input vector inversion selecting circuit41, and (2) an inversion & comparator section COMPi in an inversioncomparator circuit 42 compares the inverted and non-inverted values ofan output from each scalar product value calculating section Rai in ascalar product value calculating circuit 12a with each other, outputs abigger value of the two.

The input vector inversion selecting circuit 41 includes a change-overswitch SWk and an inverter Gk in accordance with each of the lines Lk.When the change-over switch SWk is conducted to a non-inversion side, aninput signal from the line Lk1 is kept non-inverted and outputted to theline Lk. On the contrary, when the change-over switch SWk is conductedto an inversion side, the input signal from the line Lk1 is inverted inrespect of its polarity by an inverter Gi and then outputted from theline Lk2 to the line Lk via the change-over switch SWk. The switchingstate of the change-over switch SWk is interlocked with each other, andcontrolled by a control circuit 45. The control circuit 45 controls thepolarity of the output from each of the scalar product value calculatingsection Rai in the inversion & comparator or section COMPi in interlockwith the switching operation of the change-over switch SWk and.

Consequently, in the scalar product value calculating sections Rai, theproduct and sum of the code components Cik of the code words Ci and thevector components xk of the input vector x, and those of the codecomponents Cik of the code words Ci and the inverted values of thevector components xk are obtained. The inversion & comparator sectionCOMPi compares the non-inverted values and inverted values of the outputfrom corresponding scalar product value calculating section Rai, andoutputs a bigger output to the maximum input detecting circuit 21. Also,a switching element Tbi is provided in accordance with each of theinversion & comparator sections COMPi in the same manner as theswitching elements Ti. When the output line Yi of a correspondingchannel of the maximum input detecting circuit 21 is in a high level,the switching element Tbi conducts and outputs to the output selectingcircuit 18b a code fb indicating whether the output from thecorresponding inversion & comparator section COMPi to the maximum inputdetecting circuit 21 is a non-inverted value or an inverted value.

Therefore, the scalar product values of both the non-inverted andinverted values of the input vector x are calculated with the code wordsCi. The calculation is equivalent to calculation of the scalar productvalues of the input vector x with the code words Ci and -Ci. Thisenables the code words Ci to increase by 1 bit, that is, the number i ofthe code words to double, without increasing the area needed formounting capacitors, thereby carrying out the vector quantization withhigh precision and efficiency.

Attention should be paid where the image compressing apparatus 1b isprovided with the low band buffer circuit 43 for sampling the outputfrom a mean value calculating circuit 11 at a predetermined cycle togenerate a vector, and a low band vector quantization circuit 44 forquantizing that vector. Therefore, in the image compressing apparatus1b, when necessary, the output from the mean value calculating circuit11 is scalar-quantized and then outputted by an A/D converter 14, orvector-quantized and then outputted by the low band buffer circuit 43and low band vector quantization circuit 44.

For example, as shown in FIG. 10, a predetermined number j (j=1, 2, . .. ; and in the example shown in FIG. 10, j=4) of the compressionprocessing unit blocks 7 are designated as one low band compressionprocessing unit block 8. Mean value vectors xL1, xL2, . . . aregenerated for every low band compression processing unit block 8 bysampling the mean value μ in the compression processing unit blocks 7with the low band buffer circuit 43 at every number j of the compressionprocessing unit blocks 7. These mean value vectors xL1, xL2 . . . arethen vector-quantized with the mean-separated normalized vectorquantization method in the low band vector quantization circuit 44.

FIG. 11 is a block diagram showing an electric arrangement of the lowband buffer circuit 43. The low band buffer circuit 43, mainly has ashift register 51 and a sample & hold section 52. The sample & holdsection 52 is composed of four sample & hold circuits SH1, SH2, SH3 andSH4 in accordance with the number j of the dimension of the mean valuevectors xL1, xL2, . . . .

In response to, for example, a clock signal from a control section (notshown), the shift register 51 derives trigger signals in a sequentialmanner to lines LB1 through LB4 which correspond to the sample & holdcircuits SH1 through SH4 in a respective manner. The output from themean value calculating circuit 11 is fed commonly to the sample & holdcircuits SH1 through SH4 via the line LA. In response to the triggersignals, the sample & hold circuits SH1 through SH4 carry out samplingof the output from the mean value calculating circuit 11 in a sequentialmanner, and derives hold outputs to lines LL1 to LL4. As shown in FIG.10, the mean values p of the processing unit blocks 7 in the low bandcompression processing unit blocks 8 are thus read in in a sequentialmanner, and the mean value vectors xL1, xL2, . . . can be generated.

The sample & hold circuit SH1 can be realized by, for example, anarrangement shown in FIG. 12. This sample & hold circuit SH1 includes aregister 53 and amplifier 54 which constitute an input circuit forconverting an output current from the mean value calculating circuit 11into a voltage, a switch 55 for sampling an output from the amplifier 54in response to the trigger signal, a register 56, capacitor 57, andamplifier 58 for holding an output from the switch 55. The other sample& hold circuits SH2 through SH4 can be arranged in the same manner.

The low band vector quantization circuit 44 receives as vectorcomponents voltage levels inputted from the low band buffer circuit 43via the lines LL1 through LL4, and carries out mean-separated normalizedvector quantization. The low band vector quantization circuit 44 has asimilar arrangement to that of the image compressing apparatus 1b minusthe low band vector quantization circuit 44, low band buffer circuit 43and output selecting circuit 18b. In other words, The low band vectorquantization circuit 44 can be arranged in the same manner as is a highband vector quantization section 46 which is composed of the inputvector inversion selecting circuit 41, the mean value calculatingcircuit 11, the scalar product calculating circuit 12a, the inversioncomparator circuit 42, a high band maximum scalar product valuedetecting circuit 13b, a high band index encoding circuit 16b, the A/Dconverters 14 and 15, a comparator 17, and the control circuit 45.

FIG. 13 is a block diagram showing an electric arrangement of the lowband vector quantization circuit 44. The signals inputted via the liensLL1 through LL4 are changed-over for non-inverted and inverted valuesalternatively by an input vector inversion selecting circuit 41L, andinputted to a low band mean value calculating circuit 11L. A mean valuecalculated by the low band mean value calculating circuit 11L isscalar-quantized by an A/D converter 14L and then inputted to the outputselecting circuit 18b.

A low band scalar product value calculating circuit 12L for calculatingscalar product values with respect to the input vectors xL1, xL2, . . .composed of the input signals is provided with scalar product valuecalculating sections RL.o slashed.. The number of the scalar productvalue calculating sections RL.o slashed. corresponds to the number .oslashed. (.o slashed.=1, 2, . . . , Φ) of the code words. The scalarproduct value calculating section RL.o slashed. is composed of anamplifier for sum and product calculation and capacitors correspondingto the code components.

The inversion comparator circuit 42L controlled in interlock with theinput vector inversion selecting circuit 41L by a control circuit 45Lcompares inverted and non-inverted values of the output from the scalarproduct value calculating section RL.o slashed. with each other, and abigger value of the two is inputted to the low band maximum scalarproduct value detecting circuit 13L. A high-level output is derived froma maximum input detecting circuit 21L in the low band maximum scalarproduct value detecting circuit 13L only to the channel yielding amaximum value among output lines YL.o slashed. corresponding to thescalar product value calculating sections RL.o slashed.. Next, the indexIL of the channel to which that output is derived is encoded by the lowband index encoding circuit 16L, and outputted to the output selectingcircuit 18b. A code fL corresponding to the uppermost bit of the indexIL representing whether the scalar product value here is a non-invertedor inverted value is inputted to the output selecting circuit 18b via aswitching element TLb.o slashed.. Moreover, a voltage levelcorresponding to the result of the calculation of the scalar productvalue of the channel yielding the maximum scalar product is inputtedfrom the switching element TLb.o slashed. to an A/D converter 15L,quantized and then inputted to the output selecting circuit 18b.

As shown in FIG. 9, the output selecting circuit 18b receives aquantization code of a high band mean value μ from the A/D converter 14in the high band vector quantization section 46, a quantization code ofthe absolute value of a high band maximum scalar product value P fromthe A/D converter 15, a code fb of the high band maximum scalar productvalue P from the high band maximum scalar product value detectingcircuit 13b, an index I from the high band index encoding circuit 16b,and a flag f from the comparator circuit 17. Meanwhile, the outputselecting circuit 18b receives a quantization code of a low band meanvalue μL from the A/D converter 14L in the low band vector quantizationcircuit 44, a quantization code of the absolute value of a low bandmaximum scalar product value PL from the A/D converter 15L, a code fL ofthe low band maximum scalar product value PL from the low band maximumscalar product value detecting circuit 13L, and an index IL from the lowband index encoding circuit 16L. The output selecting circuit 18b, asshown in FIGS. 14 and 15, selectively outputs these codes and the indexto the output line 3 as the code data in response to the flag f.

The code data outputted to the output line 3 are, for example, given toand transmitted by a transmitter, or given to and recorded by arecording apparatus. Therefore, the code data received by a receiver orreproduced by a reproducing apparatus are, first, decoded from the lowband mean value μL, the low band index IL, and the low band maximumscalar product value PL into the image signals representing the meanvalue μ for every low band compression processing unit block 8. Next, inaccordance with the judgement flag f, the signal level xk of each pixelis decoded from the index I and the maximum scalar product value P forevery compression processing unit block 7 if the judgement flag f is 1,whereas the signal level xk is decoded with the mean value μ if thejudgement flag f is 0. The decoded signal levels xk are sequentiallyarranged to be at places predetermined on the image to be decoded, and adecoded image is thus produced.

Note that the output selecting circuit 18b may be arranged to output themean value μ, the mean value μL obtained from the mean value μ, theindex IL, the maximum scalar product value PL, and the maximum scalarproduct value code fL selectively as necessary. For example, if thearrangement of the decoding side is to be simplified, the mean value μmay be transmitted. If the decoding side is arranged to be capable ofdecoding low band components which are vector-quantized with themean-separated normalized vector quantization method, the mean value μL,the index IL, the maximum scalar product value PL, and the maximumscalar product value code fL may be outputted.

FIGS. 14 and 15 are a flow chart illustrating compressing operation ofthe image compressing apparatus 1b arranged in the above manner. FIG. 14shows operation of the high band vector quantization section 46, whichis similar to the entire operation of the image compressing apparatus 1shown in FIG. 4. Therefore, corresponding segments are indicated by thesame reference numerals and description thereof is omitted.

In the high band vector quantization section 46, a correction valuecorresponding to quantization error in mounting the code componentcapacitors Hik (i=1 through 32, k=1 through 36) as shown in Eq. (18) isobtained as illustrated in γ 6b from the mean value μ obtained in thestep β1 and illustrated in γ 2. In the step β3b, scalar product valuesof the input signal c with each of the code words C1 through C32 arecalculated, and the calculated results are corrected by the correctionvalues mentioned above to obtain the scalar product values (X, Ci).

In the step β7b, the polarity of the scalar product value (X, Ci) isinverted, and the inverted and non-inverted values are compared witheach other. The absolute values |(X, Ci)| of the scalar product valuesof the input signal x with respect of the code words C1 through C32 arethus obtained. In the step β4, the maximum scalar product value P andits index are obtained. In the step β5, the maximum scalar product valueP is compared with the threshold value Vthl, and the judgment flag isset or reset in accordance with the result of the comparison.

In the step β6b, in response to the judgement flag f, as illustrated inγ 5b, for example, the judgement flag of 1 bit, the index I of 5 bits,the quantization code of the maximum scalar product value of 3 bits andthe maximum scalar product value code fb of 1 bit are outputted per 36pixels if the judgement flag f is 1, whereas only the judgement flag fis outputted per 36 pixels if the judgement flag f is 0. The mean valuesμ are sampled by the low band buffer circuit 43 as discussed above, andinputted to the low band vector quantization circuit 44 as the inputsignal xL.

FIG. 15 is a flow chart illustrating compressing operation of the lowband components of the low band vector quantization circuit 44. Thisoperation is similar to the operation shown in FIG. 14, and therefore,corresponding segments in the FIG. 15 are indicated by the samereference numerals of two digits with the addition of the subscript L.As shown in FIG. 10, the low band buffer circuit 43 inputs 4-dimensionalinput signals xL illustrated in γ1L for every low band compressionprocessing unit block 8 composed of 4 blocks of the mean values μ of thecompression processing unit blocks 7. The input signals xL are forexample, set to have resolution of 256 gradations.

In the step β1L, the mean value μL of the input signals xL iscalculated, and the low band mean value calculating circuit 11L outputsmean value signals illustrated in γ2L.

Meanwhile, the code words CL1 through CL32 which are realized in eachscalar product value calculating section RL.o slashed.(.o slashed.=32)by the normalized code component capacitors as illustrated in γ4L areformed in the scalar product calculating circuit 12L. The scalar productvalues of the input signals xL with each of the code words CL1 throughCL32 are calculated by the scalar product value calculating section β3L.From the results of the calculation, the correction values of thequantization error generated in accordance with the mean value μ asillustrated in γ6L are added to obtain the scalar product values (XL,CL.o slashed.).

Meanwhile, in the step β7L, as in the step β7b, the polarity of thescalar product value (XL, CL.o slashed.) is inverted, and the invertedand non-inverted values are compared with each other to obtain theabsolute value |(XL, CL.o slashed.)| of the scalar product value. In thestep β4L, as in the step β4, the maximum scalar product value isdetected, and its maximum scalar product value PL and index IL areobtained. In the step β6L, as illustrated in γ5L, for example, the meanvalue μL of 5 bits, the index IL of 5 bits, the maximum scalar productvalue PL of 4 bits and the code fL of the maximum scalar product valueof 1 bit are outputted per 144 pixels.

As discussed above, the image compressing apparatus 1b also receives themean value μ of every compression processing unit block 7 as the inputvector xL for every compression processing unit block 8, carries out themean-separated normalized vector quantization, and outputs the results.Therefore, the data amount having the mean value μ can be compressedwithout damaging the image quality. In other words, the data amount wascompressed to 15 bits per 144 pixels in the example shown in FIG. 15,whereas the data amount was compressed to 5 bits per 36 pixels in theexample shown in FIG. 4 discussed above.

In the above embodiments, calculation for the mean values, scalarproduct values and so on are carried out with analog circuits.Nonetheless, as another embodiment in accordance with the presentinvention, a digital circuit may carry out that calculation after theinputted image signal is converted from analog to digital. Moreover,instead of the arrangement show n in FIG. 3, the maximum outputdetecting circuit 21 may employ a different arrangement: for example,the arrangement suggested in the Japanese Patent Application No.7-125372/1995 (Tokuganhei 7-125372) previously filed by the sameinventors with the present invention.

The invention being thus described, it will be obvious that the same maybe varied in many ways. Such variations are not to be regarded as adeparture from the spirit and scope of the invention, and all suchmodifications as would be obvious to one skilled in the art intended tobe include within the scope of the following claims.

What is claimed is:
 1. An image compressing apparatus for receivingimage signals as an input vector for every predetermined compressionprocessing unit block and compressing the image signals with amean-separated normalized vector quantization method, comprising:aplurality of scalar product value calculating sections for calculatingscalar product values of a difference component vector and a code word,the difference component vector being generated by subtracting a meanvalue of vector components of the input vector from each of the vectorcomponents, the code word being generated from image signals of aplurality of kinds of predetermined images for learning; ascalar-quantization section for scalar-quantizing the mean value and amaximum scalar product value; an encoding section for encoding anidentification number of one of the code words, the code word yieldingthe maximum scalar product value through the calculation by said scalarproduct value calculating section; a low band buffer for generating alow band vector for every low band compression processing unit blockcomposed of a plurality of compression processing block units byreceiving the mean values at a predetermined cycle; a low band vectorquantization section for vector-quantizing the low band vector with themean-separated normalized vector quantization method; a comparatorsection for judging whether the maximum scalar product value is not lessthan a predetermined threshold value; and an output selecting sectionfor, in accordance with the judgement by said comparator section,outputting the quantization code of the maximum scalar product valuefrom said scalar quantization section, the identification code of thecode word from said encoding section, a quantization code of a low bandmean value, a quantization code of a low band maximum scalar productvalue and a low band identification code, i. e., an identificationnumber of the code word yielding the low band maximum scalar productvalue when the maximum scalar product value is not less than thethreshold value, and outputting the quantization code of the low bandmean value, the quantization code of the low band maximum scalar productvalue, and the low band identification code, wherein said outputselecting section selectively outputs the quantization code of the meanvalue from said scalar quantization section, a quantization code of thelow band mean value obtained by further vector-quantizing the mean valuewith the mean-separated normalized vector quantization method, thequantization code of the low band maximum scalar product value and thelow band identification code.
 2. The image compressing apparatus asdefined in claim 1,wherein said low band buffer includes:a shiftregister for shifting a control signal and outputting the control signalas trigger signals in a sequential manner; and a plurality of sample &hold circuits for sampling and holding the mean value in accordance withthe trigger signals from the shift register, and said low band vectorquantization section includes:said scalar product value calculatingsections; said scalar quantization section; said encoding section; andsaid comparator section.
 3. The image compressing apparatus as definedin claim 1,wherein each of said scalar product value calculatingsections includes an amplifier and capacitors corresponding to codecomponents of each of the code words, wherein said scalar product valuecalculating section calculates scalar product values of the input vectorand each of the code words in a parallel manner for each of the codewords by inputting input signals of a plurality of channelscorresponding to the vector components to a terminal of each of thecapacitors and connecting the other terminals of the capacitors commonlyto the amplifier.
 4. The image compressing apparatus as defined in claim3,wherein capacities of the capacitors are set in a capacity ratio asthe quantized code components, wherein each of said scalar product valuecalculation sections includes a correction capacitor corresponding toquantization error caused by the capacitor and inputs a product of aelectrostatic capacity of the correction capacitor and the mean value tothe amplifier as a correction value.
 5. The image compressing apparatusas defined in claim 1, further comprising:an input vector inversionselecting section for inverting polarity of the input vector andselectively changing-over obtained inverted and non-inverted values tobe outputted; and an inversion & comparator section for, in accordancewith the change-over operation of said input vector inversion selectingsection, comparing the two scalar product values calculated by saidscalar product value calculating section using the non-inverted andinverted values with each other, and outputting a greater scalar productvalue of the two and the code of the greater scalar product value. 6.The image compressing apparatus as defined in claim 1,wherein the codeword is one of a plurality of vectors for learning obtained inaccordance with inputted image signals, the vector for learning having apower greater than a predetermined threshold value and great change inimages in the compression processing unit blocks.
 7. An imagecompressing apparatus for receiving image signals as an input vector forevery predetermined compression processing unit block and compressingthe image signals with a mean-separated normalized vector quantizationmethod, comprising:a mean value calculating section for calculating amean value of vector components of the input vector; a mean valueseparating section for generating a difference component vector bysubtracting the calculated mean value from each of the vector componentsof the input vector; a memory section for storing vectors for learninggenerated from image signals of a plurality of kinds of predeterminedimages for learning as code words; a scalar product value calculatingsection for calculating scalar product values of the differencecomponent vector and each of the code words; a maximum scalar productvalue detecting section for detecting one of the code words, the codeword yielding a maximum scalar product value through the calculation; amean value quantization section for scalar-quantizing the mean value; again quantization section for scalar-quantizing the maximum scalarproduct value; a vector encoding section for encoding an identificationnumber of the code word yielding the maximum scalar product value; a lowband buffer for generating a low band vector for every low bandcompression processing unit block composed of a plurality of compressionprocessing block units by receiving the mean values at a predeterminedcycle; a low band vector quantization section for vector-quantizing thelow band vector with the mean-separated normalized vector quantizationmethod; a comparator section for judging whether the maximum scalarproduct value is not less than a predetermined threshold value; and anoutput selecting section for, in accordance with the judgement by saidcomparator section, outputting the quantization code of the maximumscalar product value from said gain quantization section, theidentification code of the code word from said vector encoding section,a quantization code of a low band mean value, a quantization code of alow band maximum scalar product value and a low band identificationcode, i. e., an identification number of the code word yielding the lowband maximum scalar product value, instead of the quantization code ofthe mean value when the maximum scalar product value is not less thanthe threshold value, and outputting the quantization code of the lowband mean value, the quantization code of the low band maximum scalarproduct value and the low band identification code when the maximumscalar product value is less than the threshold value, wherein saidoutput selecting section selectively outputs the quantization code ofthe mean value from said mean value quantization section, a quantizationcode of the low band mean value obtained by further vector-quantizingthe mean value with the mean-separated normalized vector quantizationmethod, the quantization code of the low band maximum scalar productvalue and the low band identification code.
 8. The image compressingapparatus as defined in claim 7,wherein said low band buffer includes:ashift register for shifting a control signal and outputting the controlsignal as trigger signals in a sequential manner; and a plurality ofsample & hold circuits for sampling and holding the mean value inaccordance with the trigger signals from the shift register, and saidlow band vector quantization section includes: said scalar product valuecalculating sections; said scalar quantization section; said encodingsection; and said comparator section.
 9. The image compressing apparatusas defined in claim 7,wherein each of said scalar product valuecalculating sections includes an amplifier and capacitors correspondingto code components of each of the code words, wherein said scalarproduct value calculating section calculates scalar product values ofthe input vector and each of the code words in a parallel manner foreach of the code words by inputting input signals of a plurality ofchannels corresponding to the vector components to a terminal of each ofthe capacitors and connecting the other terminals of the capacitorscommonly to the amplifier.
 10. The image compressing apparatus asdefined in claim 9,wherein capacities of the capacitors are set in acapacity ratio as the quantized code components, wherein each of saidscalar product value calculation sections includes a correctioncapacitor corresponding to quantization error caused by the capacitorand inputs a product of a electrostatic capacity of the correctioncapacitor and the mean value to the amplifier as a correction value. 11.The image compressing apparatus as defined in claim 7, furthercomprising:an input vector inversion selecting section for invertingpolarity of the input vector and selectively changing-over obtainedinverted and non-inverted values to be outputted; and an inversion &comparator section for, in accordance with the change-over operation ofsaid input vector inversion selecting section, comparing the two scalarproduct values calculated by said scalar product value calculatingsection using the non-inverted and inverted values with each other, andoutputting a greater scalar product value of the two and the code of thegreater scalar product value.
 12. The image compressing apparatus asdefined in claim 7,wherein the code word is one of a plurality ofvectors for learning obtained in accordance with inputted image signals,the vector for learning having a power greater than a predeterminedthreshold value and great change in images in the compression processingunit blocks.
 13. An image compressing apparatus for receiving imagesignals as an input vector for every predetermined compressionprocessing unit block and compressing the image signals with amean-separated normalized vector quantization method, comprising:aplurality of scalar product value calculating sections for calculatingscalar product values of a difference component vector and a code word,the difference component vector being generated by subtracting a meanvalue of vector components of the input vector from each of the vectorcomponents, the code word being generated from image signals of aplurality of kinds of predetermined images for learning; an input vectorinversion selecting section for inverting polarity of the input vectorand selectively changing-over obtained inverted and non-inverted valuesto be outputted; an inversion & comparator section for, in accordancewith the change-over operation of said input vector inversion selectingsection, comparing the two scalar product values calculated by saidscalar product value calculating section using the non-inverted andinverted values with each other, and outputting a greater scalar productvalue of the two and the code of the greater scalar product value; ascalar-quantization section for scalar-quantizing the mean value and amaximum scalar product value; an encoding section for encoding anidentification number of one of the code words, the code word yieldingthe maximum scalar product value through the calculation by said scalarproduct value calculating section; a comparator section for judgingwhether the maximum scalar product value is not less than apredetermined threshold value; and an output selecting section for, inaccordance with the judgement by said comparator section, outputting thequantization code of the mean value from said scalar quantizationsection, the quantization code of the maximum scalar product value fromsaid scalar quantization section and the identification code of the codeword from said encoding section when the maximum scalar product value isnot less than the threshold value, and outputting only the quantizationcode of the mean value when the maximum scalar product value is lessthan the threshold value.
 14. An image compressing apparatus forreceiving image signals as an input vector for every predeterminedcompression processing unit block and compressing the image signals witha mean-separated normalized vector quantization method, comprising:amean value calculating section for calculating a mean value of vectorcomponents of the input vector; a mean value separating section forgenerating a difference component vector by subtracting the calculatedmean value from each of the vector components of the input vector; amemory section for storing vectors for learning generated from imagesignals of a plurality of kinds of predetermined images for learning ascode words; a scalar product value calculating section for calculatingscalar product values of the difference component vector and each of thecode words; an input vector inversion selecting section for invertingpolarity of the input vector and selectively changing-over obtainedinverted and non-inverted values to be outputted; an inversion &comparator section for, in accordance with the change-over operation ofsaid input vector inversion selecting section, comparing the two scalarproduct values calculated by said scalar product value calculatingsection using the non-inverted and inverted values with each other, andoutputting a greater scalar product value of the two and the code of thegreater scalar product value; a maximum scalar product value detectingsection for detecting one of the code words, the code word yielding amaximum scalar product value through the calculation; a mean valuequantization section for scalar-quantizing the mean value; a gainquantization section for scalar-quantizing the maximum scalar productvalue; a vector encoding section for encoding an identification numberof the code word yielding the maximum scalar product value; a comparatorsection for judging whether the maximum scalar product value is not lessthan a predetermined threshold value; and an output selecting sectionfor, in accordance with the judgement by said comparator section,outputting the quantization code of the mean value from said mean valuequantization section, the quantization code of the maximum scalarproduct value from said gain quantization section and the identificationcode of the code word from said vector encoding section when the maximumscalar product value is not less than the threshold value, andoutputting only the quantization code of the mean value when the maximumscalar product value is less than the threshold value.